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Artificial Neural Networks for Internal Combustion Engine Performance and Emission Analysis

International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 87 - Number 6
Year of Publication: 2014
Anant Bhaskar Garg
Parag Diwan
Mukesh Saxena

Anant Bhaskar Garg, Parag Diwan and Mukesh Saxena. Article: Artificial Neural Networks for Internal Combustion Engine Performance and Emission Analysis. International Journal of Computer Applications 87(6):23-27, February 2014. Full text available. BibTeX

	author = {Anant Bhaskar Garg and Parag Diwan and Mukesh Saxena},
	title = {Article: Artificial Neural Networks for Internal Combustion Engine Performance and Emission Analysis},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {87},
	number = {6},
	pages = {23-27},
	month = {February},
	note = {Full text available}


This paper presents an analytical work for better design system that contributes to the reduction of fuel consumption and emission for vehicle performance. The main technological issue on engines today is to comply with emission standards with cost-effective measures in order to keep the engine price still attractive to customer. The experimental research of engine performance are time consuming and quite expensive. The purpose of this work is to optimize engine performance using artificial neural networks (ANN). Back propagation neural network was used to optimize prediction model performance. The paper analyzed data from various experimental tests in which different engine operating parameters are measured. The paper highlights the framework and suitable model of ANN to optimize several operating parameters of the engine. The optimization includes a range of standards engine-operating conditions, with specified limits in emissions.


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